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Interactive survival analysis with the OCDM system: From development to application

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Abstract

Medical data mining is currently actively pursued in computer science and statistical research but not in medical practice. The reasons therefore lie in the difficulties of handling and statistically analyzing medical data. We have developed a system that allows practitioners in the field to interactively analyze their data without assistance of statisticians or data mining experts. In the course of this paper we will introduce data mining of medical data and show how this can be achieved for survival data. We will demonstrate how to solve common problems of interactive survival analysis by presenting the Online Clinical Data Mining (OCDM) system. Thereby the main focus is on similarity based queries, a new method to select similar cases based on their covariables and the influence of these on their survival.

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Notes

  1. OnLine Analytical Processing—A hypothesis driven, dimensional approach to decision support (Kimball 1996).

  2. The terms knowledge discovery in databases (KDD) and data mining (DM) are used in accordance with Fayyad et al. (1996). When it comes to actual software systems we will use the terms data mining or knowledge discovery system variantly.

  3. In this paper we use the term data warehouse in a broader sense, as a storage system for a large number of information from different sources.

  4. A non-parametric method to estimate the conditional expectation of a random variable Y, given the value x of its covariate, by a locally weighted average of the observations Y i related to the vicinity of x which is moderated by a kernel function and a bandwidth, see Hastie et al. (2002), e.g.

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Authors and Affiliations

  1. Intelligent Systems Department, Stuttgart University, Universitätsstrasse 38, 70569, Stuttgart, Germany

    Sebastian Klenk & Gunther Heidemann

  2. Department of Mathematics, Institute for Stochastics and Applications (ISA), Stuttgart University, Pfaffenwaldring 57, 70569, Stuttgart, Germany

    Jürgen Dippon

  3. Robert-Bosch-Krankenhaus Stuttgart, Institute for Digital Medicine, Auerbachstrasse 110, 70376, Stuttgart, Germany

    Peter Fritz

Authors
  1. Sebastian Klenk
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  2. Jürgen Dippon
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  3. Peter Fritz
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  4. Gunther Heidemann
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Correspondence to Sebastian Klenk.

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Klenk, S., Dippon, J., Fritz, P. et al. Interactive survival analysis with the OCDM system: From development to application. Inf Syst Front 11, 391–403 (2009). https://doi.org/10.1007/s10796-009-9152-5

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